Dynamic Product Assembly and Inventory Control for Maximum Profit

We consider a manufacturing plant that purchases raw materials for product assembly and then sells the final products to customers. There are M types of raw materials and K types of products, and each product uses a certain subset of raw materials for assembly. The plant operates in slotted time, and every slot it makes decisions about re-stocking materials and pricing the existing products in reaction to (possibly time-varying) material costs and consumer demands. We develop a dynamic purchasing and pricing policy that yields time average profit within epsilon of optimality, for any given epsilon>0, with a worst case storage buffer requirement that is O(1/epsilon). The policy can be implemented easily for large M, K, yields fast convergence times, and is robust to non-ergodic system dynamics.Comment: 32 page

Decision support for build-to-order supply chain management through multiobjective optimization

This is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.Brunel Research Initiative and Enterprise Fund (BRIEF

Decision support for build-to-order supply chain management through multiobjective optimization

This paper aims to identify the gaps in decision-making support based on multiobjective optimization for build-to-order supply chain management (BTOSCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting multiobjective optimization (MOO) techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted and future research directions to better exploit the decision support capabilities of MOO are proposed

Evolution of a supply chain management game for the trading agent competition

TAC SCM is a supply chain management game for the Trading Agent Competition (TAC). The purpose of TAC is to spur high quality research into realistic trading agent problems. We discuss TAC and TAC SCM: game and competition design, scientific impact, and lessons learnt

Bottleneck co-ownership as a regulatory alternative

This paper proposes a regulatory mechanism for vertically related industries in which the upstream “bottleneck” segment faces significant returns to scale while other (downstream) segments may be more competitive. In the proposed mechanism, the ownership of the upstream firm is allocated to downstream firms in proportion to their shares of input purchases. This mechanism, while preserving downstream competition, partially internalizes the benefits of exploiting economies of scale resulting from an increase in downstream output. We show that this mechanism is more efficient than a disintegrated market structure in which the upstream natural monopoly bottleneck sets a price equal to average cost.Regulation, vertically related industries, co-ownership

Product bundling in global ocean transportation

There are over 20 'components' in an international door-to-door transportation, ranging from warehousing and distribution, to forwarding, documentation, transportation, customs clearance, etc..As tariffs in ocean transportation tend to converge due to competition and service homogenization, carriers, in competition with third party logistics service providers, strive to integrate door-to-door services under their control. In doing so, and among others, they invest heavily in logistics rather than ships that can nowadays be easily chartered in from institutional investors.Integration efforts however have been met with varying degrees of success in the face of skeptical and suspicious shippers requiring cost break down and more transparency. With the use of game theory, this paper attempts to develop winning service bundling strategies for ocean carriers, i.e. global supply chain solutions under all-in prices. Preliminary results show that, under certain conditions, bundling can be an equilibrium strategy for one or more carriers, and despite leveraging around captive liner services and potentially enhanced profits, bundling does not necessarily lead to a loss in social welfare.bundling;integrated logistics;liner shipping;vertical integration

Revenue Management and Demand Fulfillment: Matching Applications, Models, and Software

Recent years have seen great successes of revenue management, notably in the airline, hotel, and car rental business. Currently, an increasing number of industries, including manufacturers and retailers, are exploring ways to adopt similar concepts. Software companies are taking an active role in promoting the broadening range of applications. Also technological advances, including smart shelves and radio frequency identification (RFID), are removing many of the barriers to extended revenue management. The rapid developments in Supply Chain Planning and Revenue Management software solutions, scientific models, and industry applications have created a complex picture, which appears not yet to be well understood. It is not evident which scientific models fit which industry applications and which aspects are still missing. The relation between available software solutions and applications as well as scientific models appears equally unclear. The goal of this paper is to help overcome this confusion. To this end, we structure and review three dimensions, namely applications, models, and software. Subsequently, we relate these dimensions to each other and highlight commonalities and discrepancies. This comparison also provides a basis for identifying future research needs.Manufacturing;Revenue Management;Software;Advanced Planning Systems;Demand Fulfillment

Revenue Management In Manufacturing: A Research Landscape

Revenue management is the science of using past history and current levels of order activity to forecast demand as accurately as possible in order to set and update pricing and product availability decisions across various sales channels to maximize profitability. In much the same way that revenue management has transformed the airline industry in selling tickets for the same flight at markedly different rates based upon product restrictions, time to departure, and the number of unsold seats, many manufacturing companies have started exploring innovative revenue management strategies in an effort to improve their operations and profitability. These strategies employ sophisticated demand forecasting and optimization models that are based on research from many areas, including management science and economics, and that can take advantage of the vast amount of data available through customer relationship management systems in order to calibrate the models. In this paper, we present an overview of revenue management systems and provide an extensive survey of published research along a landscape delineated by three fundamental dimensions of capacity management, pricing, and market segmentation

The research for flexible product family manufacturing based on real options

Purpose: The goal of this paper is to find the best production strategy for product portfolio, which means the largest value of the options. And finally, give a case and find the solution of the optimal production strategy for product portfolio. Design/methodology/approach: This article, based on the production with characteristics of a call option and 0-1 integer programming model, build new-product portfolio strategy, and through case demonstrate that traditional method underestimates the value of the product portfolio. Finding: According to market being volatility and uncertainty and the production can being delayed, firms can flexibly arrange the best time for products to manufacture. Use real options theory to analyze product decision and the best production timing decision. Find the total options value is higher than the traditional methods. Research limitations/implications: We are not applied to real option pricing theory in modular flexible production system. We just applied real option pricing theory to the product platform. The basic model need to improve. While the thinking of this paper provides some research ideas for flexible production systems based on real option in further research.Peer Reviewe